Use of Low-Value Radiotherapy Practices in Canada: An Analysis of Provincial Cancer Registry Data
Bibliographic record
Abstract
BACKGROUND: As part of Choosing Wisely Canada (a national campaign to encourage patient-provider conversations about unnecessary medical tests, treatments, and procedures), a list of ten oncology practices that could be low-value in some instances was developed. Of those practices, two were specific to radiation therapy (rt): conventional fractionation as part of breast-conserving therapy (bct) for women with early-stage breast cancer, and multifraction radiation for palliation of uncomplicated painful bone metastases. Here, we report baseline findings for the current utilization rates of those two rt practices in Canada. RESULTS: The use of conventional fractionation as part of bct varied substantially from province to province. Of women 50 years of age and older, between 8.8% (Alberta) and 36.5% (Saskatchewan) received radiation in 25 fractions (excluding boost irradiation) as part of bct. The use of hypofractionated rt (that is, 16 fractions excluding boost irradiation)-a preferred approach for many patients-was more common in all 6 reporting provinces, ranging from 43.2% in Saskatchewan to 94.7% in Prince Edward Island. The use of multifraction rt for palliation of bone metastases also varied from province to province, ranging from 40.3% in British Columbia to 69.0% in Saskatchewan. The most common number of fractions delivered to bone metastases was 1, at 50.2%; the second most common numbers were 2-5 fractions, at 41.7%. CONCLUSIONS: Understanding variation in the use of potentially low-value rt practices can help to inform future strategies to promote higher-value care, which balances high-quality care with the efficient use of limited system resources. Further work is needed to understand the factors contributing to the interprovincial variation observed and to develop benchmarks for the appropriate rate of use of these rt practices.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.019 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".